Optimization of Functionally Graded Beams Resting on Elastic Foundations

Journal of Solid Mechanics

مقاله 6، دوره 3، شماره 4، اسفند 2011، صفحه 365-378   

نوع مقاله: Research Paper

نویسندگان

M.H Yas^{* 1}؛ S Kamarian¹؛ J.E Jam²؛ A Pourasghar¹

¹Department of Mechanical Engineering, Razi University, Kermanshah

²Center for Composite Materials & Structures, MUT, Tehran

چکیده

In this study, two goals are followed. First, by means of the Generalized Differential Quadrature (GDQ) method, parametric analysis on the vibration characteristics of three-parameter Functionally Graded (FG) beams on variable elastic foundations is studied. These parameters include (a) three parameters of power-law distribution, (b) variable Winkler foundation modulus, (c) two-parameter elastic foundation modulus. Then, volume fraction optimization of FG beam with respect to the fundamental frequency is studied. Since the optimization process is so complicated and time consuming, Genetic Algorithm (GA), a computational algorithm based on Darwinian theories that allow to solve optimization problems without using gradient-based information on the objective functions and the constraints, is performed to obtain the best material profile through the thickness to maximize the first natural frequency. A proper Artificial Neural Network (ANN) is trained by training data sets obtained from GDQ method and then is applied as the objective function in genetic algorithm by reproducing the fundamental frequency for improving the speed of the optimization process. Finally, the optimized material profile for the maximum natural frequency of a FG beam resting on elastic foundations is presented.

کلیدواژه‌ها

Functionally graded beam؛ Elastic foundations؛ Optimization؛ Genetic Algorithm؛ Artificial Neural Network

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